152 citations
- Carnegie Mellon UniversityUS5 papers
- Ludwig-Maximilians-Universität MünchenDE5 papers
- Center for Strategic ResearchRU4 papers
- Robotic Research (United States)US4 papers
- LMU KlinikumDE3 papers
- Optim Design (United States)US3 papers
- Aalborg UniversityDK2 papers
- Centre for Arctic Gas Hydrate, Environment and ClimateNO2 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- Columbia UniversityUS2 papers
- Stanford UniversityUS2 papers
- UiT The Arctic University of NorwayNO2 papers
4 papers · 2 filters
On Cold Posteriors of Probabilistic Neural Networks: Understanding the Cold Posterior Effect and A New Way to Learn Cold Posteriors with Tight Generalization Guarantees
Yijie Zhang
Bayesian inference provides a principled probabilistic framework for quantifying uncertainty by updating beliefs based on prior knowledge and observed data through Bayes' theorem.…
Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients
Youssef Allouah, Abdellah El Mrini, Rachid Guerraoui +2
Federated learning (FL) is an appealing paradigm that allows a group of machines (a.k.a. clients) to learn collectively while keeping their data local. However, due to the heteroge…
Temporal Graph ODEs for Irregularly-Sampled Time Series
Alessio Gravina, Daniele Zambon, Davide Bacciu +1
Modern graph representation learning works mostly under the assumption of dealing with regularly sampled temporal graph snapshots, which is far from realistic, e.g., social network…
Corrective Machine Unlearning
Shashwat Goel, Ameya Prabhu, Philip Torr +2
Machine Learning models increasingly face data integrity challenges due to the use of large-scale training datasets drawn from the Internet. We study what model developers can do i…